Arrival time prediction systems for public transportation
are often developed with the use of modern wireless telecom-
munications, including wireless sensor networks (WSNs) [ 1 –
6 ]. A WSN is composed of a large number of inexpensive
microsensor nodes deployed in the monitoring area [ 7 ,
8 ] and communicates via wireless communication [ 9 ]. A
WSN is easy to deploy, programmable, and dynamically
reconfigurable [ 10 , 11 ].
WSNs are also suitable for applications that require
network provision system environments that are fast, easy,
or impossible to preestablish; WSNs can gradually replace
the traditional sensor application systems that are monitored
using artificial methods. WSNs can efficiently and automati-
cally retrieve data using wireless network transmission.
Existing bus arrival time prediction systems transmit the
data collected to centralized servers. However, this type of
system has considerable overhead in bus systems in fairly
developed areas. Because many buses drive on roads simul-
taneously, a significant amount of data is sent to the server in
certainperiods.Theservermustanalyzeandcalculatethese
data to predict the arrival time of each bus. These data must
be processed and sent in real time, so they cannot be delayed
by any system overhead; otherwise, the prediction accuracy
will be affected.
This paper proposes a method of combining a peer-to-
peer (P2P) overlay network and WSN to develop a bus arrival
time prediction system. A P2P overlay network is added to
traditional prediction systems to allow for real-time data.
Each bus is installed with a sensor, and each bus stop can
receive data sent from sensors. Due to the distance limitation
of sensors, the sensors on buses and the data-receiving device
of a bus station form a single WSN environment. All bus
stations and station termini are connected to form a P2P
overlay network, which is used to transmit real-time bus
information and predict bus arrival times. Through the WSN
technology, bus stations retrieve data from buses and transmit
these data to subsequent bus stations to estimate the bus
arrival times. This approach can be a powerful tool for
monitoring and predicting traffic conditions.
The advantage of using P2P overlay networks to connect
bus stations is that each bus station can act as a client and
server to exchange information for nearby buses. Through
this method, the data collected from buses do not need to
be transmitted from bus stations to a centralized server and
could be evaluated such that bus stations can predict the
arrival time. This paper adopts an Arrangement Graph-based
Overlay network (AGO) [ 12 , 13 ]asourP2Poverlaynetwork
because this system performs well in transmitting messages.
By combining P2P overlay networks and WSNs, this study
considers a novel approach to predict bus arrival times and
presents some initial results of this endeavor.
Some experiments were performed to demonstrate the
performance of our bus arrival time prediction system com-
pared to existing prediction systems; the experimental results
revealed that our bus arrival time prediction system can make
more accurate predictions. Although there are several factors
that can affect the accuracy of our bus arrival time prediction
system, such as the time of day and number of passengers,
our prediction system is more convenient and provides more
information for passengers than existing prediction systems,
particularly paper timetables. The number of messages trans-
mitted to the centralized server and the system overhead of
the centralized service are both reduced considerably.
The remainder of this paper is organized as follows.
Section 2presents some related work on WSNs, P2P over-
lay networks, and AGO systems.Section 3describes the
proposed bus arrival time prediction system, and some
experimental results are presented inSection 4.Finally,the
conclusions of this study and potential avenues for future
work are discussed inSection 5.2. Related Work
In this section, some studies related to our proposed system
are introduced. Our bus arrival time prediction system
is developed by using WSNs and P2P overlay networks,
and thus some properties related to these technologies are
introduced.2.1. Wireless Sensor Networks.Duetotherapidadvance-
ments in microfabrication, communication, and embedded
processing, small, sophisticated electronic devices can be
embedded with sensing, computing, and communicating
functions. Therefore, WSNs have become a popular research
topic in computer science. WSNs mainly include sensing,
communicating, and computing aspects (i.e., hardware, soft-
ware, and algorithms, resp.). A WSN is a network system
composed of several wireless data receivers and sensors,
and communication between these components is wireless
communication. To achieve large-scale deployment, WSN
devices should be inexpensive, small, and easy to deploy and
should have low power consumption [ 14 , 15 ]. These devices
also need to have sensing, programmability, and dynamic
reconfiguration capabilities because sensors rely on the power
of batteries to supply the energy necessary for operations
and radio transmission distance. Sensor nodes transmit and
receive data via wireless technology, and sensor networks are
largely used for short-distance data transmission to reduce
power consumption.
The development of WSNs initially originated in military
applications, such as battlefield monitoring by the University
of California, Berkeley (UC, Berkeley), for a research project
calledSmartDust[ 16 ] funded by the United States Defense
Research Projects Agency (DARPA). Many manufactur-
ers have followed the direction of research by combining
IEEE 802.15.4 low-rate wireless personal area networks (LR-
WPANs) and ZigBee [ 17 , 18 ].
Many standard applications use common wireless com-
munication technologies, including automated home devices,
online shopping [ 19 ], environment safety and control, and
personal health care [ 20 , 21 ].2.2. Peer-to-Peer Overlay Network.In the recent past, an
information system was typically a single server that handled
all requests from clients and all responses to them. Clients
hadtofirsttalktotheservertoestablishcommunication
channels and then sent requests to the server for processing.
If there was any information that needed to be communicated